NMR in Biomedicine

Anisotropic water diffusion in neural fibres such as nerve, white matter in spinal cord, or white matter in brain forms the basis for the utilization of diffusion tensor imaging (DTI) to track fibre pathways. The fact that water diffusion is sensitive to the underlying tissue microstructure provides a unique method of assessing the orientation and integrity of these neural fibres, which may be useful in assessing a number of neurological disorders. The purpose of this review is to characterize the relationship of nuclear magnetic resonance measurements of water diffusion and its anisotropy (i.e. directional dependence) with the underlying microstructure of neural fibres. The emphasis of the review will be on model neurological systems both in vitro and in vivo. A systematic discussion of the possible sources of anisotropy and their evaluation will be presented followed by an overview of various studies of restricted diffusion and compartmentation as they relate to anisotropy. Pertinent pathological models, developmental studies and theoretical analyses provide further insight into the basis of anisotropic diffusion and its potential utility in the nervous system. Copyright © 2002 John Wiley & Sons, Ltd.

The state of the art of reconstruction of the axonal tracts in the central nervous system (CNS) using diffusion tensor imaging (DTI) is reviewed. This relatively new technique has generated much enthusiasm and high expectations because it presently is the only approach available to non‐invasively study the three‐dimensional architecture of white matter tracts. While there is no doubt that DTI fiber tracking is providing exciting new opportunities to study CNS anatomy, it is very important to understand its limitations. In this review we therefore assess the basic principles and the assumptions that need to be made for each step of the study, including both data acquisition and the elaborate fiber reconstruction algorithms. Special attention is paid to situations where complications may arise, and possible solutions are reviewed. Validation issues and potential future directions and improvements are also discussed. Copyright © 2002 John Wiley & Sons, Ltd.

The LCModel method analyzes an in vivo spectrum as a Linear Combination of Model in vitro spectra from individual metabolite solutions. Complete model spectra, rather than individual resonances, are used in order to incorporate maximum prior information into the analysis. A nearly model‐free constrained regularization method automatically accounts for the baseline and lineshape in vivo without imposing a restrictive parameterized form on them. LCModel is automatic (non‐interactive) with no subjective input. Approximately maximum‐likelihood estimates of the metabolite concentrations and their uncertainties (Cramér‐Rao lower bounds) are obtained. LCModel analyses of spectra from users with fields from 1.5 to 9.4 T and a wide range of sequences, particularly with short TE, are used here to illustrate the capabilities and limitations of LCModel and proton MRS. Copyright © 2001 John Wiley & Sons, Ltd. Ala

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We review several methods that have been developed to infer microstructural and physiological information about isotropic and anisotropic tissues from diffusion weighted images (DWIs). These include Diffusion Imaging (DI), Diffusion Tensor Imaging (DTI), isotropically weighted imaging, and q‐space imaging. Just as DI provides useful information about molecular displacements in one dimension with which to characterize diffusion in isotropic tissues, DTI provides information about molecular displacements in three dimensions needed to characterize diffusion is anisotropic tissues. DTI also furnishes scalar parameters that behave like quantitative histological or physiological‘stains’ for different features of diffusion. These include Trace(D), which is related to the mean diffusivity, and a family of parameters derived from the diffusion tensor, D, which characterize different features of anisotropic diffusion. Simple thought experiments and geometrical constructs, such as the diffusion ellipsoid, can be used to understand water diffusion in isotropic and anisotropic media, and the NMR experiments used to characterize it.

Molecular and cellular MR imaging is a rapidly growing field that aims to visualize targeted macromolecules or cells in living organisms. In order to provide a different signal intensity of the target, gadolinium‐based MR contrast agents can be employed although they suffer from an inherent high threshold of detectability. Superparamagnetic iron oxide (SPIO) particles can be detected at micromolar concentrations of iron, and offer sufficient sensitivity for T₂(*)‐weighted imaging. Over the past two decades, biocompatible particles have been linked to specific ligands for molecular imaging. However, due to their relatively large size and clearance by the reticuloendothelial system (RES), widespread biomedical molecular applications have yet to be implemented and few studies have been reproduced between different laboratories. SPIO‐based cellular imaging, on the other hand, has now become an established technique to label and detect the cells of interest. Imaging of macrophage activity was the initial and still is the most significant application, in particular for tumor staging of the liver and lymph nodes, with several products either approved or in clinical trials. The ability to now also label non‐phagocytic cells in culture using derivatized particles, followed by transplantation or transfusion in living organisms, has led to an active research interest to monitor the cellular biodistribution in vivo including cell migration and trafficking. While most of these studies to date have been mere of the ‘proof‐of‐principle’ type, further exploitation of this technique will be aimed at obtaining a deeper insight into the dynamics of in vivo cell biology, including lymphocyte trafficking, and at monitoring therapies that are based on the use of stem cells and progenitors. Copyright © 2004 John Wiley & Sons, Ltd.

This article treats the theoretical underpinnings of diffusion‐tensor magnetic resonance imaging (DT‐MRI), as well as experimental design and data analysis issues. We review the mathematical model underlying DT‐MRI, discuss the quantitative parameters that are derived from the measured effective diffusion tensor, and describe artifacts thet arise in typical DT‐MRI acquisitions. We also discuss difficulties in identifying appropriate models to describe water diffusion in heterogeneous tissues, as well as in interpreting experimental data obtained in such issues. Finally, we describe new statistical methods that have been developed to analyse DT‐MRI data, and their potential uses in clinical and multi‐site studies. Copyright © 2002 John Wiley & Sons, Ltd.

Manganese‐enhanced MRI (MEMRI) is being increasingly used for MRI in animals due to the unique T₁ contrast that is sensitive to a number of biological processes. Three specific uses of MEMRI have been demonstrated: to visualize activity in the brain and the heart; to trace neuronal specific connections in the brain; and to enhance the brain cytoarchitecture after a systemic dose. Based on an ever‐growing number of applications, MEMRI is proving useful as a new molecular imaging method to visualize functional neural circuits and anatomy as well as function in the brain in vivo. Paramount to the successful application of MEMRI is the ability to deliver Mn²⁺ to the site of interest at an appropriate dose and in a time‐efficient manner. A major drawback to the use of Mn²⁺ as a contrast agent is its cellular toxicity. Therefore, it is critical to use as low a dose as possible. In the present work the different approaches to MEMRI are reviewed from a practical standpoint. Emphasis is given to the experimental methodology of how to achieve significant, yet safe, amounts of Mn²⁺ to the target areas of interest. Copyright © 2004 John Wiley & Sons, Ltd.

Diffusion NMR is the only method available today that noninvasively provides information on molecular displacements over distances comparable to cell dimensions. This information can be used to infer tissue microstructure and microdynamics. However, data may be fairly difficult to interpret in biological tissues which differ markedly from the theoretical “infinite isotrope medium”, as many factors may affect the NMR signal. The object of this paper is to analyze the expected effects of temperature, restriction, hindrance, membrane permeability, anisotropy and tissue inhomogeneity on the diffusion measurements. Powerful methods, such as q‐space imaging, diffusion tensor imaging and diffusion spectroscopy of metabolites further enhance the specificity of the information obtained from diffusion NMR experiments.

Quantitative susceptibility mapping (QSM) is a recently developed MRI technique that provides a quantitative measure of tissue magnetic susceptibility. To compute tissue magnetic susceptibilities based on gradient echoes, QSM requires reliable unwrapping of the measured phase images and removal of contributions caused by background susceptibilities. Typically, the two steps are performed separately. Here, we present a method that simultaneously performs phase unwrapping and HARmonic (background) PhasE REmovaL using the LAplacian operator (HARPERELLA). Both numerical simulations and in vivo human brain images show that HARPERELLA effectively removes both phase wraps and background phase, whilst preserving all low spatial frequency components originating from brain tissues. When compared with other QSM phase preprocessing techniques, such as path‐based phase unwrapping followed by background phase removal, HARPERELLA preserves the tissue phase signal in gray matter, white matter and cerebrospinal fluid with excellent robustness, providing a convenient and accurate solution for QSM. The proposed algorithm is provided, together with QSM and susceptibility tensor imaging (STI) tools, in a shared software package named ‘STI Suite’. Copyright © 2013 John Wiley & Sons, Ltd.